RESEARCH AND PRACTICE
Racial/Ethnic and Socioeconomic Differences in Short-Term Breast Cancer Survival Among Women in an Integrated Health System Theresa H. M. Keegan, PhD, MS, Allison W. Kurian, MD, MSc, Kathleen Gali, MPH, Li Tao, MD, PhD, MS, Daphne Y. Lichtensztajn, MD, MPH, Dawn L. Hershman, MD, MS, Laurel A. Habel, PhD, Bette J. Caan, DrPH, and Scarlett L. Gomez, PhD, MPH
Breast cancer is the most common cancer among women in the United States, and it is the second leading cause of cancer death.1 Despite significant improvements in breast cancer survival from 1992 to 2009,1,2 racial/ethnic and socioeconomic survival disparities have persisted.3,4 African American women have consistently been found to have worse survival after breast cancer,3,5---11 Hispanic women have worse or similar survival,3,9,11,12 and Asian women as an aggregated group have better or similar survival3,9,11,12 than do non-Hispanic White women. Underlying factors thought to contribute to these racial/ethnic disparities include differences in stage at diagnosis,8,12,13 distributions of breast cancer subtypes,14---16 comorbidities,12,13,17 access to and utilization of quality care,13,18 and treatment.12,13 Numerous studies also have found poorer survival after breast cancer diagnosis among women residing in neighborhoods of lower socioeconomic status (SES).6,9,19,20 Research has shown that inadequate use of cancer screening services, and consequent late stage diagnosis and decreased survival, contribute to the SES disparities.21,22 Similar to racial/ ethnic disparities, SES disparities have been attributed to inadequate treatment and follow-up care and comorbidities.18 Previous populationbased studies have continued to observe racial/ ethnic survival disparities after adjusting for neighborhood SES, but these studies have not considered the combined influence of neighborhood SES and race/ethnicity.3,9,11,12,23 These disparities may remain because information on individual-level SES, health insurance coverage, comorbidities, quality of care, and detailed treatment regimens have typically not been available.3,8,9,11,13 Even among studies using national Surveillance Epidemiology and End Results---Medicare linked data, in which more detailed information on treatment and
Objectives. We examined the combined influence of race/ethnicity and neighborhood socioeconomic status (SES) on short-term survival among women with uniform access to health care and treatment. Methods. Using electronic medical records data from Kaiser Permanente Northern California linked to data from the California Cancer Registry, we included 6262 women newly diagnosed with invasive breast cancer. We analyzed survival using multivariable Cox proportional hazards regression with follow-up through 2010. Results. After consideration of tumor stage, subtype, comorbidity, and type of treatment received, non-Hispanic White women living in low-SES neighborhoods (hazard ratio [HR] = 1.28; 95% confidence interval [CI] = 1.07, 1.52) and African Americans regardless of neighborhood SES (high SES: HR = 1.44; 95% CI = 1.01, 2.07; low SES: HR = 1.88; 95% CI = 1.42, 2.50) had worse overall survival than did non-Hispanic White women living in high-SES neighborhoods. Results were similar for breast cancer–specific survival, except that African Americans and non-Hispanic Whites living in high-SES neighborhoods had similar survival. Conclusions. Strategies to address the underlying factors that may influence treatment intensity and adherence, such as comorbidities and logistical barriers, should be targeted at low-SES non-Hispanic White and all African American patients. (Am J Public Health. 2015;105:938–946. doi:10. 2105/AJPH.2014.302406)
comorbidities are available among some patients aged 65 years and older, survival disparities have remained.12,23,24 However, not all data on medical conditions and health care services are captured in Medicare claims, including data on Medicare beneficiaries enrolled in HMOs (health maintenance organizations).25,26 Using electronic medical records data from Kaiser Permanente Northern California (KPNC) linked to data from the population-based California Cancer Registry (CCR), we recently reported that chemotherapy use followed practice guidelines but varied by race/ethnicity and neighborhood SES in this integrated health system.27 Therefore, to overcome the limitations of previous studies and address simultaneously the multiple social28 and clinical factors affecting survival after breast cancer diagnosis, we used the linked KPNC---CCR database to determine whether racial/ethnic and socioeconomic
938 | Research and Practice | Peer Reviewed | Keegan et al.
differences in short-term overall and breast cancer---specific survival persist in women in a membership-based health system. Our study is the first, to our knowledge, to consider the combined influence of neighborhood SES and race/ethnicity and numerous prognostic factors, including breast cancer subtypes and comorbidities, thought to underlie these longstanding survival disparities among women with uniform access to health care and treatment.
METHODS Women eligible for the study were all 6581 female residents of 23 California counties in the San Francisco Bay Area and the central valley of California who were members of KPNC when newly diagnosed with invasive breast cancer (morphology codes C50.0---C50.9 of International Classification of Diseases for
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Oncology. 3rd ed.29) during 2004 to 2007. From this group, we excluded patients with inflammatory carcinoma (n = 49), Paget’s disease (n = 2), no mass or tumor found (n = 13), a non---first primary cancer (n = 195), rare histological subtypes (n = 52), and survival time less than 1 day (n = 8). The final study population included 6262 patients.
Data Sources and Linkage KPNC members constitute nearly one third of the local population and are generally comparable to the underlying population in terms of race/ethnicity and SES.30---33 We extracted KPNC records on newly diagnosed breast cancer between 1999 and 2007 for linkage to CCR tumor-level data, as described previously.27 KPNC chemotherapy infusion databases became fully implemented in 2004; therefore, our analyses are restricted to 2004 to 2007. We used KPNC pharmacy records to identify filled prescriptions for endocrine therapy of breast cancer, including tamoxifen and aromatase inhibitors.27,34 In addition, from KPNC chemotherapy infusion databases, we extracted data on chemotherapy drug names, infusion dates, and number of infusions, focusing on the 2 most active drug classes for breast cancer, anthracycliness and taxanes.27 We did not consider the use of the monoclonal antibody trastuzumab (Herceptin) because it was not Food and Drug Administration approved for adjuvant treatment of stages I---III human epidermal growth factor receptor 2 (HER2)--positive breast cancer until 2006.27 We used KPNC data on diagnoses associated with inpatient and outpatient encounters to identify comorbidities present from 12 months before to 1 month after diagnosis and to create the Charlson Comorbidity Index.35---37 The CCR is a Surveillance Epidemiology and End Results population-based registry that has collected data about all primary cancers diagnosed among California residents since 1988. Demographic and tumor information is abstracted from medical records according to standard protocols38 in which CCR data have been described.39 Information includes age and marital status at diagnosis, race/ethnicity, tumor size, presence of lymph node involvement, cancer stage according to the American Joint Committee on Cancer classification system,40
tumor grade, subtype, and first course cancer treatments including surgery and radiation, vital status (routinely determined by the CCR through hospital follow-up and database linkages) as of December 31, 2010, and, for the deceased, the underlying cause of death. For this cohort, most clinical information is derived from the KPNC cancer registry; however, CCR data may incorporate additional reports from facilities outside KPNC.27 We categorized breast cancer subtypes according to tumor expression of estrogen receptor (ER), progesterone receptor (PR), HER2, and tumor grade.41,42 We defined (1) low-risk, endocrine-positive tumors as PR-positive, HER2-negative, and well or moderately differentiated tumor grade; (2) higher-risk, endocrine-positive tumors as ER-positive or PR-positive and any of PR-negative, HER2positive, or poorly or undifferentiated tumor grade; (3) HER2-positive, endocrine-negative tumors as ER-negative, PR-negative, and HER2-positive; and (4) triple-negative tumors as ER-negative, PR-negative, and HER2-negative. Our race/ethnicity and neighborhood SES findings were similar when we considered another definition of breast cancer subtypes.43-- 45
Neighborhood Socioeconomic Status Neighborhood SES is a previously developed composite index determined by US Census 2000 block groups in California.46 In the SES measure, we employed principal components analysis to develop a single index from 7 US Census 2000 block group indicator variables (education index, median household income, percentage living 200% below poverty level, percentage blue-collar workers, percentage older than aged 16 years in workforce without a job, median rent, and median house value).46 We classified neighborhood SES into quintiles on the basis of the distribution of the index across the state of California and then into 2 categories: low SES (quintiles 1, 2, and 3) and high SES (quintiles 4 and 5). Because of our previous findings showing interactions between race/ethnicity and neighborhood SES,27 we combined the 2 variables to explore their interactive effects on survival.
Statistical Analysis We used Cox proportional hazards regression to estimate survival hazard ratios (HRs)
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and associated 95% confidence intervals (CIs) to evaluate the impact of factors on overall and breast cancer---specific survival. For deceased patients, we measured survival time in days from the date of diagnosis to the date of death from any cause for analyses of all-cause survival or to the date of death from breast cancer for analyses of breast cancer---specific survival. We censored patients who died from other causes at the time of death for analyses of breast cancer---specific survival. We censored patients alive at the study end date (December 31, 2010) at this time or at the date of last follow-up (i.e., last known contact). We examined the proportional hazards assumption by statistical testing of the correlation between weighted Schoenfeld residuals and logarithmically transformed survival time. We did not observe any violations of the assumption. Because proportional hazards varied by stage at diagnosis (American Joint Committee on Cancer stages I---IV and unknown), we included stage as a stratifying variable in all Cox regression models, allowing the baseline hazard to vary across stage. We adjusted all models for clustering by block group. The base model included age and marital status at diagnosis in all models because these variables were of interest a priori. We grouped other significant covariates in unadjusted models, including subtype, tumor size, lymph node involvement, Charlson Comorbidity Index, and treatment modalities, and we added them sequentially into the multivariate models to assess their impact on the HR estimate of the combined race/ethnicity and neighborhood SES variable. The fully adjusted model includes age, marital status, and all the significant covariates in the unadjusted models. We carried out all statistical tests using SAS version 9.3 (SAS Institute, Cary, NC). All P values reported were 2 sided, and we considered those that were < .05 to be statistically significant.
RESULTS Our study had up to 7 years of follow-up (mean = 4.8 years; SD = 1.4 years). The majority of women were non-Hispanic White (67.7), were married (58.5), resided in high-SES neighborhoods (63.9), and were diagnosed with breast cancer when aged between 45 and
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64 years (51.2; Table 1). Most women were diagnosed with the low-risk (37.1) or higherrisk (28.2) endocrine-positive breast cancer subtypes, stage I (50.4) or II (34.5) disease and had no comorbid diagnosis (77.0). Slightly fewer than half received radiation therapy (49.7) and chemotherapy (45.5). Breast cancer accounted for 50.2% of the deaths (16.4%; n = 1028). With the exception of African Americans, 61.4% of whom were living in a low-SES neighborhood, most women were predominately living in high-SES neighborhoods (52.7% of Hispanics; 67.0% of non-Hispanic Whites; 71.8% of Asian/Pacific Islander [API]; Table 1). African Americans, regardless of neighborhood SES, were more likely than was any other racial/ethnic group to be diagnosed with a triple-negative subtype. Hispanics residing in low-SES neighborhoods had a 6.7% higher triple-negative subtype than did Hispanics residing in high-SES neighborhoods. The distribution of the triple-negative subtype was similar across high- and low-SES neighborhoods for the other racial/ethnic groups. The highest percentages of deaths occurred in African Americans and non-Hispanic Whites living in low-SES neighborhoods.
Overall Survival Non-Hispanic Whites living in low-SES neighborhoods (HR = 1.27; 95% CI = 1.06, 1.51) and African Americans, regardless of neighborhood SES (high SES: HR = 1.62; 95% CI = 1.14, 2.32; low SES: HR = 2.05; 95% CI = 1.56, 2.70) had significantly worse overall survival than did non-Hispanic Whites living in high-SES neighborhoods after adjusting for age, marital status, subtype, stage, and tumor characteristics (Table 2, model 1). Additionally adjusting for treatment and comorbidities did not appreciably change the associations for non-Hispanic Whites in low-SES neighborhoods and somewhat attenuated the associations for African Americans (Table 2, model 3). Hispanics and APIs, regardless of neighborhood SES, had overall survival similar to that of non-Hispanic Whites living in high-SES neighborhoods (Table 2, models 1, 2, and 3). When we limited analyses to women with stages I, II, or III disease, results for non-Hispanic Whites and African Americans living in low-SES neighborhoods (data not shown) were similar
to those for non-Hispanic Whites living in high-SES neighborhoods, but they were attenuated for African Americans in high-SES neighborhoods (HR = 1.29; 95% CI = 0.87, 1.93; data not shown in tables). In fully adjusted models (Table 3), worse overall survival also was associated with non---low-risk, endocrinepositive breast cancer subtypes and Charlson comorbidity score (vs a score of 0) but not marital status.
Breast Cancer–Specific Survival Non-Hispanic Whites (HR = 1.29; 95% CI = 1.01, 1.65) and African Americans (HR = 2.26; 95% CI = 1.58, 3.24) living in low-SES neighborhoods had worse breast cancer---specific survival than did non-Hispanic Whites living in high-SES neighborhoods after adjustment for age, marital status, subtype, stage, and tumor characteristics (Table 2, model 1). Additionally adjusting for treatment and comorbidities did not appreciably attenuate survival differences by neighborhood SES for non-Hispanic Whites, but the survival differences were no longer statistically significant. Adjusting for treatment and comorbidities somewhat attenuated the survival differences for African Americans in low-SES neighborhoods compared with non-Hispanic Whites in high-SES neighborhoods (Table 2, model 3). Hispanics and APIs, regardless of neighborhood SES, had breast cancer---specific survival rates that were similar to non-Hispanic Whites living in high-SES neighborhoods. When analyses were limited to women with stages I, II, or III disease, results were somewhat stronger for non-Hispanic Whites (HR = 1.35; 95% CI = 1.02, 1.80) and African Americans (HR = 2.29; 95% CI = 1.47, 3.55) living in low-SES neighborhoods than for non-Hispanic Whites living in high-SES neighborhoods (data not shown in tables). In fully adjusted models (Table 3), worse breast cancer survival was associated with non---low-risk, endocrine-positive breast cancer subtypes and a Charlson comorbidity score of 2 or higher (vs a score of 0).
DISCUSSION In our study of 6262 women with breast cancer in an integrated health care system, we found that non-Hispanic White women living in low-SES neighborhoods and African
940 | Research and Practice | Peer Reviewed | Keegan et al.
Americans, regardless of neighborhood SES, had poorer short-term overall survival than did non-Hispanic White women living in high-SES neighborhoods. Results were similar for breast cancer---specific survival, with the exception that African Americans and non-Hispanic Whites living in high-SES neighborhoods had similar breast cancer---specific survival. Hispanics and APIs, regardless of neighborhood SES, had overall and breast cancer---specific survival rates similar to those of non-Hispanic Whites living in high-SES neighborhoods. Racial/ethnic and socioeconomic disparities are thought to result from differences in breast cancer tumor biology and other characteristics3,5---8,13; comorbidities12,13,17; access to, quality of, and utilization of care13,18; and treatment.12,13 Our findings suggest access to care, tumor stage, subtype, comorbidities, and type of treatment received do not eliminate racial/ethnic and socioeconomic differences in survival after breast cancer. Although the women in our study were members of the same integrated health care system, thus equalizing access to quality health care services, women of all race/ethnic and neighborhood SES groups likely do not perceive their access equally or use health services similarly.47 For example, medical mistrust47 and perceived discrimination48,49 may be more frequent among underserved or minority groups because of negative health system experiences, leading to lower utilization of needed health care.47 Although equal access refers to equal cost or no cost at the point of access,47 there are still copayments and other costs associated with care that may be more of a barrier for low-SES groups. Most breast cancer treatments, especially those administered in an adjuvant setting, require multiple administrations and trips to the clinic (chemotherapy, radiation) or require long-term administration (endocrine therapy). Women of low SES may be more likely to face logistical barriers, such as the inability to take time off work, transportation issues, childcare obligations, or lack of social support, that make it difficult for them to adhere to these treatments.50---53 The poorer survival among African Americans and similar or better survival among Hispanics and APIs observed in our study generally are consistent with previous analyses3,9--13,23 that
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1782 (28.5) 2388 (38.1)
55–64 ‡ 65
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1732 (27.7)
Previously married
230 (8.1)
607 (21.4)
1314 (21.0)
Triple negative
Unknown
982 (15.7) 459 (7.3)
‡2
268 (4.3)
Unknown 203 (3.2) 6059 (96.8)
No
Yes
Surgery
3059 (48.9) 2935 (46.9)
No Yes
Endocrine therapy
4821 (77.0)
1
2763 (97.4)
74 (2.6)
114 (4.0)
1282 (45.2) 1441 (50.8)
184 (6.5)
427 (15.1)
2226 (78.5)
45 (1.6)
142 (2.3)
0 (no comorbidity)
Charlson Comorbidity Index
277 (9.8) 72 (2.5)
958 (33.8)
1485 (52.3)
618 (9.9) 195 (3.1)
2149 (34.3)
II
III IV
3158 (50.4)
I
AJCC tumor stage
Unclassified
273 (4.4) 588 (9.4)
HER2-positive, endocrine negative
104 (3.7) 224 (7.9)
2321 (37.1) 1766 (28.2)
1118 (39.4) 784 (27.6)
29 (1.0)
760 (26.8)
331 (11.7)
1717 (60.5)
846 (29.8) 1179 (41.6)
582 (20.5)
Low-risk, endocrine positive Higher risk, endocrine positive
Subtype
c
70 (1.1)
797 (12.7)
Never married
Unknown
3663 (58.5)
Married
Marital status at diagnosis
668 (10.7) 1424 (22.7)
45–54
No. of cases (%) (n = 6262)
< 45
Age at diagnosis, y
Demographic and Clinical Characteristics
High SESa(n = 2837), No. (%)
1355 (96.8)
45 (3.2)
76 (5.4)
660 (47.1) 664 (47.4)
113 (8.1)
240 (17.1)
1047 (74.8)
35 (2.5)
133 (9.5) 46 (3.3)
483 (34.5)
703 (50.2)
294 (21.0)
124 (8.9)
61 (4.4)
541 (38.6) 380 (27.1)
11 (0.8)
514 (36.7)
169 (12.1)
706 (50.4)
410 (29.3) 623 (44.5)
261 (18.6)
106 (7.6)
Low SES (n = 1400), No. (%)
Non-Hispanic White (n = 4237)
9 (4.9)
172 (93.0)
13 (7.0)
Racial/Ethnic and Socioeconomic Differences in Short-Term Breast Cancer Survival Among Women in an Integrated Health System Theresa H. M. Keegan, PhD, MS, Allison W. Kurian, MD, MSc, Kathleen Gali, MPH, Li Tao, MD, PhD, MS, Daphne Y. Lichtensztajn, MD, MPH, Dawn L. Hershman, MD, MS, Laurel A. Habel, PhD, Bette J. Caan, DrPH, and Scarlett L. Gomez, PhD, MPH
Breast cancer is the most common cancer among women in the United States, and it is the second leading cause of cancer death.1 Despite significant improvements in breast cancer survival from 1992 to 2009,1,2 racial/ethnic and socioeconomic survival disparities have persisted.3,4 African American women have consistently been found to have worse survival after breast cancer,3,5---11 Hispanic women have worse or similar survival,3,9,11,12 and Asian women as an aggregated group have better or similar survival3,9,11,12 than do non-Hispanic White women. Underlying factors thought to contribute to these racial/ethnic disparities include differences in stage at diagnosis,8,12,13 distributions of breast cancer subtypes,14---16 comorbidities,12,13,17 access to and utilization of quality care,13,18 and treatment.12,13 Numerous studies also have found poorer survival after breast cancer diagnosis among women residing in neighborhoods of lower socioeconomic status (SES).6,9,19,20 Research has shown that inadequate use of cancer screening services, and consequent late stage diagnosis and decreased survival, contribute to the SES disparities.21,22 Similar to racial/ ethnic disparities, SES disparities have been attributed to inadequate treatment and follow-up care and comorbidities.18 Previous populationbased studies have continued to observe racial/ ethnic survival disparities after adjusting for neighborhood SES, but these studies have not considered the combined influence of neighborhood SES and race/ethnicity.3,9,11,12,23 These disparities may remain because information on individual-level SES, health insurance coverage, comorbidities, quality of care, and detailed treatment regimens have typically not been available.3,8,9,11,13 Even among studies using national Surveillance Epidemiology and End Results---Medicare linked data, in which more detailed information on treatment and
Objectives. We examined the combined influence of race/ethnicity and neighborhood socioeconomic status (SES) on short-term survival among women with uniform access to health care and treatment. Methods. Using electronic medical records data from Kaiser Permanente Northern California linked to data from the California Cancer Registry, we included 6262 women newly diagnosed with invasive breast cancer. We analyzed survival using multivariable Cox proportional hazards regression with follow-up through 2010. Results. After consideration of tumor stage, subtype, comorbidity, and type of treatment received, non-Hispanic White women living in low-SES neighborhoods (hazard ratio [HR] = 1.28; 95% confidence interval [CI] = 1.07, 1.52) and African Americans regardless of neighborhood SES (high SES: HR = 1.44; 95% CI = 1.01, 2.07; low SES: HR = 1.88; 95% CI = 1.42, 2.50) had worse overall survival than did non-Hispanic White women living in high-SES neighborhoods. Results were similar for breast cancer–specific survival, except that African Americans and non-Hispanic Whites living in high-SES neighborhoods had similar survival. Conclusions. Strategies to address the underlying factors that may influence treatment intensity and adherence, such as comorbidities and logistical barriers, should be targeted at low-SES non-Hispanic White and all African American patients. (Am J Public Health. 2015;105:938–946. doi:10. 2105/AJPH.2014.302406)
comorbidities are available among some patients aged 65 years and older, survival disparities have remained.12,23,24 However, not all data on medical conditions and health care services are captured in Medicare claims, including data on Medicare beneficiaries enrolled in HMOs (health maintenance organizations).25,26 Using electronic medical records data from Kaiser Permanente Northern California (KPNC) linked to data from the population-based California Cancer Registry (CCR), we recently reported that chemotherapy use followed practice guidelines but varied by race/ethnicity and neighborhood SES in this integrated health system.27 Therefore, to overcome the limitations of previous studies and address simultaneously the multiple social28 and clinical factors affecting survival after breast cancer diagnosis, we used the linked KPNC---CCR database to determine whether racial/ethnic and socioeconomic
938 | Research and Practice | Peer Reviewed | Keegan et al.
differences in short-term overall and breast cancer---specific survival persist in women in a membership-based health system. Our study is the first, to our knowledge, to consider the combined influence of neighborhood SES and race/ethnicity and numerous prognostic factors, including breast cancer subtypes and comorbidities, thought to underlie these longstanding survival disparities among women with uniform access to health care and treatment.
METHODS Women eligible for the study were all 6581 female residents of 23 California counties in the San Francisco Bay Area and the central valley of California who were members of KPNC when newly diagnosed with invasive breast cancer (morphology codes C50.0---C50.9 of International Classification of Diseases for
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Oncology. 3rd ed.29) during 2004 to 2007. From this group, we excluded patients with inflammatory carcinoma (n = 49), Paget’s disease (n = 2), no mass or tumor found (n = 13), a non---first primary cancer (n = 195), rare histological subtypes (n = 52), and survival time less than 1 day (n = 8). The final study population included 6262 patients.
Data Sources and Linkage KPNC members constitute nearly one third of the local population and are generally comparable to the underlying population in terms of race/ethnicity and SES.30---33 We extracted KPNC records on newly diagnosed breast cancer between 1999 and 2007 for linkage to CCR tumor-level data, as described previously.27 KPNC chemotherapy infusion databases became fully implemented in 2004; therefore, our analyses are restricted to 2004 to 2007. We used KPNC pharmacy records to identify filled prescriptions for endocrine therapy of breast cancer, including tamoxifen and aromatase inhibitors.27,34 In addition, from KPNC chemotherapy infusion databases, we extracted data on chemotherapy drug names, infusion dates, and number of infusions, focusing on the 2 most active drug classes for breast cancer, anthracycliness and taxanes.27 We did not consider the use of the monoclonal antibody trastuzumab (Herceptin) because it was not Food and Drug Administration approved for adjuvant treatment of stages I---III human epidermal growth factor receptor 2 (HER2)--positive breast cancer until 2006.27 We used KPNC data on diagnoses associated with inpatient and outpatient encounters to identify comorbidities present from 12 months before to 1 month after diagnosis and to create the Charlson Comorbidity Index.35---37 The CCR is a Surveillance Epidemiology and End Results population-based registry that has collected data about all primary cancers diagnosed among California residents since 1988. Demographic and tumor information is abstracted from medical records according to standard protocols38 in which CCR data have been described.39 Information includes age and marital status at diagnosis, race/ethnicity, tumor size, presence of lymph node involvement, cancer stage according to the American Joint Committee on Cancer classification system,40
tumor grade, subtype, and first course cancer treatments including surgery and radiation, vital status (routinely determined by the CCR through hospital follow-up and database linkages) as of December 31, 2010, and, for the deceased, the underlying cause of death. For this cohort, most clinical information is derived from the KPNC cancer registry; however, CCR data may incorporate additional reports from facilities outside KPNC.27 We categorized breast cancer subtypes according to tumor expression of estrogen receptor (ER), progesterone receptor (PR), HER2, and tumor grade.41,42 We defined (1) low-risk, endocrine-positive tumors as PR-positive, HER2-negative, and well or moderately differentiated tumor grade; (2) higher-risk, endocrine-positive tumors as ER-positive or PR-positive and any of PR-negative, HER2positive, or poorly or undifferentiated tumor grade; (3) HER2-positive, endocrine-negative tumors as ER-negative, PR-negative, and HER2-positive; and (4) triple-negative tumors as ER-negative, PR-negative, and HER2-negative. Our race/ethnicity and neighborhood SES findings were similar when we considered another definition of breast cancer subtypes.43-- 45
Neighborhood Socioeconomic Status Neighborhood SES is a previously developed composite index determined by US Census 2000 block groups in California.46 In the SES measure, we employed principal components analysis to develop a single index from 7 US Census 2000 block group indicator variables (education index, median household income, percentage living 200% below poverty level, percentage blue-collar workers, percentage older than aged 16 years in workforce without a job, median rent, and median house value).46 We classified neighborhood SES into quintiles on the basis of the distribution of the index across the state of California and then into 2 categories: low SES (quintiles 1, 2, and 3) and high SES (quintiles 4 and 5). Because of our previous findings showing interactions between race/ethnicity and neighborhood SES,27 we combined the 2 variables to explore their interactive effects on survival.
Statistical Analysis We used Cox proportional hazards regression to estimate survival hazard ratios (HRs)
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and associated 95% confidence intervals (CIs) to evaluate the impact of factors on overall and breast cancer---specific survival. For deceased patients, we measured survival time in days from the date of diagnosis to the date of death from any cause for analyses of all-cause survival or to the date of death from breast cancer for analyses of breast cancer---specific survival. We censored patients who died from other causes at the time of death for analyses of breast cancer---specific survival. We censored patients alive at the study end date (December 31, 2010) at this time or at the date of last follow-up (i.e., last known contact). We examined the proportional hazards assumption by statistical testing of the correlation between weighted Schoenfeld residuals and logarithmically transformed survival time. We did not observe any violations of the assumption. Because proportional hazards varied by stage at diagnosis (American Joint Committee on Cancer stages I---IV and unknown), we included stage as a stratifying variable in all Cox regression models, allowing the baseline hazard to vary across stage. We adjusted all models for clustering by block group. The base model included age and marital status at diagnosis in all models because these variables were of interest a priori. We grouped other significant covariates in unadjusted models, including subtype, tumor size, lymph node involvement, Charlson Comorbidity Index, and treatment modalities, and we added them sequentially into the multivariate models to assess their impact on the HR estimate of the combined race/ethnicity and neighborhood SES variable. The fully adjusted model includes age, marital status, and all the significant covariates in the unadjusted models. We carried out all statistical tests using SAS version 9.3 (SAS Institute, Cary, NC). All P values reported were 2 sided, and we considered those that were < .05 to be statistically significant.
RESULTS Our study had up to 7 years of follow-up (mean = 4.8 years; SD = 1.4 years). The majority of women were non-Hispanic White (67.7), were married (58.5), resided in high-SES neighborhoods (63.9), and were diagnosed with breast cancer when aged between 45 and
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64 years (51.2; Table 1). Most women were diagnosed with the low-risk (37.1) or higherrisk (28.2) endocrine-positive breast cancer subtypes, stage I (50.4) or II (34.5) disease and had no comorbid diagnosis (77.0). Slightly fewer than half received radiation therapy (49.7) and chemotherapy (45.5). Breast cancer accounted for 50.2% of the deaths (16.4%; n = 1028). With the exception of African Americans, 61.4% of whom were living in a low-SES neighborhood, most women were predominately living in high-SES neighborhoods (52.7% of Hispanics; 67.0% of non-Hispanic Whites; 71.8% of Asian/Pacific Islander [API]; Table 1). African Americans, regardless of neighborhood SES, were more likely than was any other racial/ethnic group to be diagnosed with a triple-negative subtype. Hispanics residing in low-SES neighborhoods had a 6.7% higher triple-negative subtype than did Hispanics residing in high-SES neighborhoods. The distribution of the triple-negative subtype was similar across high- and low-SES neighborhoods for the other racial/ethnic groups. The highest percentages of deaths occurred in African Americans and non-Hispanic Whites living in low-SES neighborhoods.
Overall Survival Non-Hispanic Whites living in low-SES neighborhoods (HR = 1.27; 95% CI = 1.06, 1.51) and African Americans, regardless of neighborhood SES (high SES: HR = 1.62; 95% CI = 1.14, 2.32; low SES: HR = 2.05; 95% CI = 1.56, 2.70) had significantly worse overall survival than did non-Hispanic Whites living in high-SES neighborhoods after adjusting for age, marital status, subtype, stage, and tumor characteristics (Table 2, model 1). Additionally adjusting for treatment and comorbidities did not appreciably change the associations for non-Hispanic Whites in low-SES neighborhoods and somewhat attenuated the associations for African Americans (Table 2, model 3). Hispanics and APIs, regardless of neighborhood SES, had overall survival similar to that of non-Hispanic Whites living in high-SES neighborhoods (Table 2, models 1, 2, and 3). When we limited analyses to women with stages I, II, or III disease, results for non-Hispanic Whites and African Americans living in low-SES neighborhoods (data not shown) were similar
to those for non-Hispanic Whites living in high-SES neighborhoods, but they were attenuated for African Americans in high-SES neighborhoods (HR = 1.29; 95% CI = 0.87, 1.93; data not shown in tables). In fully adjusted models (Table 3), worse overall survival also was associated with non---low-risk, endocrinepositive breast cancer subtypes and Charlson comorbidity score (vs a score of 0) but not marital status.
Breast Cancer–Specific Survival Non-Hispanic Whites (HR = 1.29; 95% CI = 1.01, 1.65) and African Americans (HR = 2.26; 95% CI = 1.58, 3.24) living in low-SES neighborhoods had worse breast cancer---specific survival than did non-Hispanic Whites living in high-SES neighborhoods after adjustment for age, marital status, subtype, stage, and tumor characteristics (Table 2, model 1). Additionally adjusting for treatment and comorbidities did not appreciably attenuate survival differences by neighborhood SES for non-Hispanic Whites, but the survival differences were no longer statistically significant. Adjusting for treatment and comorbidities somewhat attenuated the survival differences for African Americans in low-SES neighborhoods compared with non-Hispanic Whites in high-SES neighborhoods (Table 2, model 3). Hispanics and APIs, regardless of neighborhood SES, had breast cancer---specific survival rates that were similar to non-Hispanic Whites living in high-SES neighborhoods. When analyses were limited to women with stages I, II, or III disease, results were somewhat stronger for non-Hispanic Whites (HR = 1.35; 95% CI = 1.02, 1.80) and African Americans (HR = 2.29; 95% CI = 1.47, 3.55) living in low-SES neighborhoods than for non-Hispanic Whites living in high-SES neighborhoods (data not shown in tables). In fully adjusted models (Table 3), worse breast cancer survival was associated with non---low-risk, endocrine-positive breast cancer subtypes and a Charlson comorbidity score of 2 or higher (vs a score of 0).
DISCUSSION In our study of 6262 women with breast cancer in an integrated health care system, we found that non-Hispanic White women living in low-SES neighborhoods and African
940 | Research and Practice | Peer Reviewed | Keegan et al.
Americans, regardless of neighborhood SES, had poorer short-term overall survival than did non-Hispanic White women living in high-SES neighborhoods. Results were similar for breast cancer---specific survival, with the exception that African Americans and non-Hispanic Whites living in high-SES neighborhoods had similar breast cancer---specific survival. Hispanics and APIs, regardless of neighborhood SES, had overall and breast cancer---specific survival rates similar to those of non-Hispanic Whites living in high-SES neighborhoods. Racial/ethnic and socioeconomic disparities are thought to result from differences in breast cancer tumor biology and other characteristics3,5---8,13; comorbidities12,13,17; access to, quality of, and utilization of care13,18; and treatment.12,13 Our findings suggest access to care, tumor stage, subtype, comorbidities, and type of treatment received do not eliminate racial/ethnic and socioeconomic differences in survival after breast cancer. Although the women in our study were members of the same integrated health care system, thus equalizing access to quality health care services, women of all race/ethnic and neighborhood SES groups likely do not perceive their access equally or use health services similarly.47 For example, medical mistrust47 and perceived discrimination48,49 may be more frequent among underserved or minority groups because of negative health system experiences, leading to lower utilization of needed health care.47 Although equal access refers to equal cost or no cost at the point of access,47 there are still copayments and other costs associated with care that may be more of a barrier for low-SES groups. Most breast cancer treatments, especially those administered in an adjuvant setting, require multiple administrations and trips to the clinic (chemotherapy, radiation) or require long-term administration (endocrine therapy). Women of low SES may be more likely to face logistical barriers, such as the inability to take time off work, transportation issues, childcare obligations, or lack of social support, that make it difficult for them to adhere to these treatments.50---53 The poorer survival among African Americans and similar or better survival among Hispanics and APIs observed in our study generally are consistent with previous analyses3,9--13,23 that
American Journal of Public Health | May 2015, Vol 105, No. 5
1782 (28.5) 2388 (38.1)
55–64 ‡ 65
May 2015, Vol 105, No. 5 | American Journal of Public Health
1732 (27.7)
Previously married
230 (8.1)
607 (21.4)
1314 (21.0)
Triple negative
Unknown
982 (15.7) 459 (7.3)
‡2
268 (4.3)
Unknown 203 (3.2) 6059 (96.8)
No
Yes
Surgery
3059 (48.9) 2935 (46.9)
No Yes
Endocrine therapy
4821 (77.0)
1
2763 (97.4)
74 (2.6)
114 (4.0)
1282 (45.2) 1441 (50.8)
184 (6.5)
427 (15.1)
2226 (78.5)
45 (1.6)
142 (2.3)
0 (no comorbidity)
Charlson Comorbidity Index
277 (9.8) 72 (2.5)
958 (33.8)
1485 (52.3)
618 (9.9) 195 (3.1)
2149 (34.3)
II
III IV
3158 (50.4)
I
AJCC tumor stage
Unclassified
273 (4.4) 588 (9.4)
HER2-positive, endocrine negative
104 (3.7) 224 (7.9)
2321 (37.1) 1766 (28.2)
1118 (39.4) 784 (27.6)
29 (1.0)
760 (26.8)
331 (11.7)
1717 (60.5)
846 (29.8) 1179 (41.6)
582 (20.5)
Low-risk, endocrine positive Higher risk, endocrine positive
Subtype
c
70 (1.1)
797 (12.7)
Never married
Unknown
3663 (58.5)
Married
Marital status at diagnosis
668 (10.7) 1424 (22.7)
45–54
No. of cases (%) (n = 6262)
< 45
Age at diagnosis, y
Demographic and Clinical Characteristics
High SESa(n = 2837), No. (%)
1355 (96.8)
45 (3.2)
76 (5.4)
660 (47.1) 664 (47.4)
113 (8.1)
240 (17.1)
1047 (74.8)
35 (2.5)
133 (9.5) 46 (3.3)
483 (34.5)
703 (50.2)
294 (21.0)
124 (8.9)
61 (4.4)
541 (38.6) 380 (27.1)
11 (0.8)
514 (36.7)
169 (12.1)
706 (50.4)
410 (29.3) 623 (44.5)
261 (18.6)
106 (7.6)
Low SES (n = 1400), No. (%)
Non-Hispanic White (n = 4237)
9 (4.9)
172 (93.0)
13 (7.0)
